By thermal image is meant an image generated by optical mapping of infrared radiation or thermal radiation. In terms of technology, a thermal image can be produced, particularly in the near infrared region by the known, conventional technologies for visible light such as by the use of CCD sensors or CMOS sensors. However, a thermal image can be generated particularly in the mid infrared and far infrared regions (definition of radiation bands according to DIN 5031, Part 7, 1984-01) by a matrix of temperature-sensitive resistors (detector elements) such as, e.g., a matrix arrangement of microbolometers. An arrangement of detector elements in a matrix (array) will be referred to hereinafter as “focal plane array” (FPA).
The recording of images is carried out in frames. By “frame” is meant that data set comprising the intensity values of the individual detector elements associated with an image at a readout time. The intensity values of the individual detector elements which are defined with respect to their level and spatial arrangement are referred to as pixels in the frames. In the following, recordings which actually represent a mapping of the environment are referred to as image frames, while recordings through which only internal reference data are acquired are referred to as background frames. Internal reference data can be acquired particularly through background frames by which a reference object is recorded.
The image frames and background frames can be modified, particularly corrected, stored and visually displayed, after readout. The (corrected) image frames and background frames are the basis for the outputted visually observable thermal images and background images.
A bias is usually applied to the individual detector elements of the FPAs which then permit a temperature-dependent current intensity. When the FPA is exposed via infrared optics, a thermal image can be realized.
However, the individual detector elements, particularly microbolometer resistors, have a non-uniform sensitivity, or non-uniformity, which results from the self-heating of each individual microbolometer which is due to biasing on the one hand and is based on manufacturing tolerances on the other hand. Owing to the non-uniform sensitivity, the data of the intensities of the pixels of every image frame contain contributions which can be considered as noise and constitute a source of error in the production of a thermal image or background image.
“Non-uniformity correction” (NUC) refers to methods by which a non-uniform sensitivity of the individual detector elements is compensated. The differences in the sensitivity of the detector elements can be greater than the intensity variations in the source image itself and must therefore always be corrected in practice in order to obtain a thermal image which reproduces a real temperature distribution. The distribution and level of the noise contributions to the individual intensities of the pixels can be derived from the background frames.
In this connection, NUC takes essentially two approaches: 1) reference-based methods using image frames which are calibrated when the camera is first put to use; and 2) scene-based methods in which the image frames are corrected continuously, or at least repeatedly, during the operation of the thermographic camera.
In known solutions, the FPA was thermostated. In more recent solutions, the substrate temperature is determined either directly by a substrate temperature sensor and/or indirectly by means of a thermally short-circuited microbolometer whose signal serves as a reference for the substrate temperature. As a rule, the two methods are used in parallel.
Regardless of whether it is based on direct or indirect measurement of the substrate temperature, the acquired substrate temperature signal can then be used to regulate the bias of the detector elements or to serve as an input variable for numerical correction based on stored calibration data.
A method for the correction of non-uniform sensitivities of detector elements is described in U.S. Pat. No. 4,298,887. The correction data are derived exclusively from the object image by means of a recursive filter and an arithmetic unit. A shutter for generating reference images by which the beam path of a thermographic camera can be occasionally closed is not provided.
In practice, shutterless methods have not yet gained acceptance. This is because the method does not deliver the desired quality of thermal images because the absolute measuring accuracy achieved is too low owing to the absence of internal reference (shutter). Also, the object scene must change regularly, which is why shutterless methods cannot be applied to fixed-installation cameras.
Conventionally, a shutter unit arranged in the beam path of the thermographic camera is closed at regular intervals interrupting the imaging beam path alternately with the recording of an image frame. The closed shutter unit is a defined object for infrared irradiation of the FPA because, in the infrared region, the shutter unit is also a radiation emitter which is parameterized by its temperature. However, the radiation physics characteristics of the shutter unit are well known. When the shutter unit is closed, the FPA delivers background frames which can be used for correcting the image frames.
A known method for correcting image frames is two-point correction. In this method, at least two frames of the same image are recorded consecutively and a—usually nonlinear—characteristic curve is generated by comparing the data of the individual pixels. This characteristic curve is approximated by a straight line which intersects the characteristic curve at least two points (two-point correction). A general linear equation can be given for an approximation of this kind:f(y)=ax+b,  (1)
where a is the gain, b is the intersection with the ordinate at x0 (offset), and f(y) is the approximated value of the data of the FPA (e.g., Harris et al., 1999, IEEE Transactions on Image Processing 8 (8: 1148-1151).
There are no stipulations, per se, as to the criteria under which the nonlinear characteristic line is approximated by the straight line, i.e., the mathematical methods on which the approximation is based. In practice, it is also very possible that the nonlinear characteristic curve is not known at all and that gain and offset are also determined without knowing it, e.g., based on a calibration. Nonlinear approximations are also known from the prior art, e.g., US 2009/0273675 A1.
US 2009/0273675 A1 discloses a method for the correction of non-uniform sensitivities of detector elements in thermographic cameras in which the beam path of a thermographic camera is interrupted periodically by a shutter unit over a shutter phase. During a first shutter phase, the output signal of each detector element is acquired by a FPA and is fed to a processor unit. Using these data, at least a first map of temperature distributions over the FPA is updated in the processor unit and a second map is made and stored in the processor unit. The data of the at least first map and the data of the second map come from different shutter phases and are approximated by the processor unit by means of a mathematical function (linear, polynomial). This function is then used to interpolate between the at least first map and the second map to compensate for variations in the data of the individual detector elements and to make a new map of the temperature distributions. Variations for each detector element can be compensated individually or for all of the detector elements with the aid of the new map.
By means of the solution according to US 2009/0273675 A1 it is possible to calibrate thermographic cameras individually, repeatedly, and also while they are in operation.
A drawback of the known prior art is that individual image frames whose data have excessive increases (peaks) in positive or negative direction exert a disproportionately great and long-lasting influence on the function used for the correction. Accordingly, data peaks whose occurrence is merely stochastic can have a long-term negative impact on the method.
Also, in practice, the existing solutions have the substantial drawback that they interrupt the recording of image frames often and for long periods of time. This greatly impairs a real-time display of thermal images. In addition, short-term fluctuations of the intensity values and noise are poorly smoothed because the thermal image recording and background recording alternate more or less evenly with one another. Possible long-term drift, i.e., changes in the display or readout data of measuring equipment which are not dependent on external influences, is not satisfactorily corrected. In order to improve both the smoothing of short-term fluctuations in intensity values and noise and the correction of long-term drift, which would naturally be desirable, many image frames and background frames would have to be stored and computed. This wastes considerable storage space and computing time. Further, the real-time image is repeatedly interrupted for long periods. This represents a substantial drawback for time-critical real-time applications.